{"type": "FeatureCollection", "features": [{"id": "10.1111/gcb.12819", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:18:00Z", "type": "Journal Article", "created": "2014-12-05", "title": "Soil Warming And Co2 Enrichment Induce Biomass Shifts In Alpine Tree Line Vegetation", "description": "Abstract

Responses of alpine tree line ecosystems to increasing atmospheric CO2 concentrations and global warming are poorly understood. We used an experiment at the Swiss tree line to investigate changes in vegetation biomass after 9\uffc2\uffa0years of free air CO2 enrichment (+200\uffc2\uffa0ppm; 2001\uffe2\uff80\uff932009) and 6\uffc2\uffa0years of soil warming (+4\uffc2\uffa0\uffc2\uffb0C; 2007\uffe2\uff80\uff932012). The study contained two key tree line species, Larix decidua and Pinus uncinata, both approximately 40\uffc2\uffa0years old, growing in heath vegetation dominated by dwarf shrubs. In 2012, we harvested and measured biomass of all trees (including root systems), above\uffe2\uff80\uff90ground understorey vegetation and fine roots. Overall, soil warming had clearer effects on plant biomass than CO2 enrichment, and there were no interactive effects between treatments. Total plant biomass increased in warmed plots containing Pinus but not in those with Larix. This response was driven by changes in tree mass (+50%), which contributed an average of 84% (5.7\uffc2\uffa0kg\uffc2\uffa0m\uffe2\uff88\uff922) of total plant mass. Pinus coarse root mass was especially enhanced by warming (+100%), yielding an increased root mass fraction. Elevated CO2 led to an increased relative growth rate of Larix stem basal area but no change in the final biomass of either tree species. Total understorey above\uffe2\uff80\uff90ground mass was not altered by soil warming or elevated CO2. However, Vaccinium myrtillus mass increased with both treatments, graminoid mass declined with warming, and forb and nonvascular plant (moss and lichen) mass decreased with both treatments. Fine roots showed a substantial reduction under soil warming (\uffe2\uff88\uff9240% for all roots <2\uffc2\uffa0mm in diameter at 0\uffe2\uff80\uff9320\uffc2\uffa0cm soil depth) but no change with CO2 enrichment. Our findings suggest that enhanced overall productivity and shifts in biomass allocation will occur at the tree line, particularly with global warming. However, individual species and functional groups will respond differently to these environmental changes, with consequences for ecosystem structure and functioning.

", "keywords": ["0106 biological sciences", "2. Zero hunger", "Models", " Statistical", "Temperature", "Larix", "Carbon Dioxide", "15. Life on land", "Pinus", "Global Warming", "01 natural sciences", "Soil", "Species Specificity", "13. Climate action", "Biomass", "Tundra", "Switzerland"]}, "links": [{"href": "https://doi.org/10.1111/gcb.12819"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcb.12819", "name": "item", "description": "10.1111/gcb.12819", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcb.12819"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-01-30T00:00:00Z"}}, {"id": "10.1128/aem.02264-23", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:18:23Z", "type": "Journal Article", "created": "2024-02-19", "title": "Novel endolithic bacteria of phylum Chloroflexota reveal a myriad of potential survival strategies in the Antarctic desert", "description": "ABSTRACT

The ice-free McMurdo Dry Valleys of Antarctica are dominated by nutrient-poor mineral soil and rocky outcrops. The principal habitat for microorganisms is within rocks (endolithic). In this environment, microorganisms are provided with protection against sub-zero temperatures, rapid thermal fluctuations, extreme dryness, and ultraviolet and solar radiation. Endolithic communities include lichen, algae, fungi, and a diverse array of bacteria. Chloroflexota is among the most abundant bacterial phyla present in these communities. Among the Chloroflexota are four novel classes of bacteria, here named Candidatus Spiritibacteria class. nov. (=UBA5177), Candidatus Martimicrobia class. nov. (=UBA4733), Candidatus Tarhunnaeia class. nov. (=UBA6077), and Candidatus Uliximicrobia class. nov. (=UBA2235). We retrieved 17 high-quality metagenome-assembled genomes (MAGs) that represent these four classes. Based on genome predictions, all these bacteria are inferred to be aerobic heterotrophs that encode enzymes for the catabolism of diverse sugars. These and other organic substrates are likely derived from lichen, algae, and fungi, as metabolites (including photosynthate), cell wall components, and extracellular matrix components. The majority of MAGs encode the capacity for trace gas oxidation using high-affinity uptake hydrogenases, which could provide energy and metabolic water required for survival and persistence. Furthermore, some MAGs encode the capacity to couple the energy generated from H 2 and CO oxidation to support carbon fixation (atmospheric chemosynthesis). All encode mechanisms for the detoxification and efflux of heavy metals. Certain MAGs encode features that indicate possible interactions with other organisms, such as Tc-type toxin complexes, hemolysins, and macroglobulins.

IMPORTANCE

The ice-free McMurdo Dry Valleys of Antarctica are the coldest and most hyperarid desert on Earth. It is, therefore, the closest analog to the surface of the planet Mars. Bacteria and other microorganisms survive by inhabiting airspaces within rocks (endolithic). We identify four novel classes of phylum Chloroflexota , and, based on interrogation of 17 metagenome-assembled genomes, we predict specific metabolic and physiological adaptations that facilitate the survival of these bacteria in this harsh environment\uffe2\uff80\uff94including oxidation of trace gases and the utilization of nutrients (including sugars) derived from lichen, algae, and fungi. We propose that such adaptations allow these endolithic bacteria to eke out an existence in this cold and extremely dry habitat.

", "keywords": ["570", "Bacteria", "Fungi", "Antarctic Regions", "Chloroflexi", "15. Life on land", "Survival strategies", "Cold Temperature", "Extremophiles", "13. Climate action", "Antarctica", "Endolithic communities", "Metagenomics", "14. Life underwater", "Sugars", "Settore BIO/19 - MICROBIOLOGIA GENERALE"]}, "links": [{"href": "https://doi.org/10.1128/aem.02264-23"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20and%20Environmental%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1128/aem.02264-23", "name": "item", "description": "10.1128/aem.02264-23", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1128/aem.02264-23"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-02-19T00:00:00Z"}}, {"id": "10.5281/zenodo.15096788", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:01Z", "type": "Dataset", "title": "HWSD2_Climate_and_Socioeconomic_agriculturalsoil_dataset_mainland_portugal", "description": "The study uses the Harmonized World Soil Database (HWSD v2.0) developed by FAO and IIASA for biophysical models and agroecological queries. This database consolidates information from various sources, including the European Soil Database, the 1:1 million soil map of China, and national soil maps from Afghanistan, Ghana, and T\u00fcrkiye. It has a spatial resolution of around 1 km and is revised in 2013 and 2023. HWSD v2.0 includes detailed information on soil mapping units, general soil unit information, and specific physical and chemical soil unit characteristics across seven depth layers. The database fields cover a wide range of attributes, such as soil texture, bulk density, organic carbon content, pH, and cation exchange capacity. The harmonization process ensures that data from different sources is standardized and integrated, providing a consistent and reliable dataset for various applications. However, the HWSD v2.0 has some limitations, such as combining soil inventories gathered at different times, scales, and precision, which may affect its reliability for national studies. It is recommended to use national-level harmonized soil databases for more accurate results in specific regions. For Portugal's mainland, the data presented in the HWSD v2.0 dataset is sourced from the European Soil Data Centre (ESDAC), which contains various metrics of chemical and physical soil properties. Out of the 2882 Portuguese parishes, only 22 are left out, representing 0.76% percent of the total number of parishes. The study uses several datasets to analyze land use and occupation in Portugal. The Land Use and Occupation Map (COS2007v3.0) is a detailed thematic map of land use and occupation for mainland Portugal, developed by the Directorate-General for Territory (DGT). The data is organized hierarchically and includes 83 classes of land use and occupation. The CHELSA database, maintained by the Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), provides bioclimatic indexes for precipitation and average temperature over various temporal intervals and variables. The National Institute of Statistics (INE) provides data on agricultural machinery distribution across different geographical locations. The dataset covers the total number of agricultural machines, as well as specific categories such as wheeled and tracked tractors, motor cultivators, power hoes, motor mowers, and combine harvesters. The dataset also examines the distribution of farms with access to irrigation based on geographical location. The burned land data from 1975 to 2023 provides a comprehensive overview of fire occurrences and their impact over time. This data is crucial for understanding long-term patterns, assessing the effectiveness of fire prevention measures, and informing future land management and policy decisions. Lastly, the population density dataset from the 2021 Census and the 2011 Census provides a decennial comparison of total population density across different geographical regions. These data are essential for understanding the evolution of land use and occupation in Portugal and their implications for environmental and agricultural consequences.", "keywords": ["Soil", "Total organic carbon", "Land use", "Soil use", "Atmospheric precipitation", "Soil type", "Organic carbon", "Land surface temperature"], "contacts": [{"organization": "Almeida Santos, R. G. F.", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15096788"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15096788", "name": "item", "description": "10.5281/zenodo.15096788", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15096788"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-03-27T00:00:00Z"}}, {"id": "10.5281/zenodo.7656722", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:34Z", "type": "Dataset", "title": "Data for: The effect of land-use change on soil C, N, P, and their stoichiometries: A global synthesis", "description": "Open AccessData description This dataset includes detailed information about five different types of land use change reported in \u201cThe effect of land-use change on soil C, N, P, and their stoichiometries: A global synthesis (Agriculture, Ecosystems and Environment; https://doi.org/10.1016/j.agee.2023.108402)\u201d. Lists of five different types of land use change 1) conversion of primary forest to cropland 2) conversion of primary forest to grassland 3) conversion of cropland to forest 4) conversion of grassland to forest 5) conversion of grassland to cropland Lists of detailed information Land use change (pre-LUC, post-LUC) Country, Location, Geographic position (Longitude, Latitude) Altitude (m) Climate zone Weather [rainfall (mm yr-1) and temperature (\u00b0C)] Reported time of change (years) Vegetation type (pre-LUC, post-LUC) Fertilizer (pre-LUC, post-LUC: type, application; change) Soil sampling depth (cm) Soil type [units, pre-LUC, post-LUC, change rate (%)] Soil pH, bulk density, CEC [units, pre-LUC, post-LUC, change rate (%)] Soil organic carbon [units, pre-LUC, post-LUC, change rate (%)] Soil total nitrogen [units, pre-LUC, post-LUC, change rate (%)] Soil total phosphorus [units, pre-LUC, post-LUC, change rate (%)] Soil C:N [units, pre-LUC, post-LUC, change rate (%)] Soil C:P [units, pre-LUC, post-LUC, change rate (%)] Soil N:P [units, pre-LUC, post-LUC, change rate (%)] Reference Data collection method We analyzed five different types of LUC: 1) conversion of primary forest to cropland, 2) conversion of primary forest to grassland, 3) conversion of cropland to forest, 4) conversion of grassland to forest, and 5) conversion of grassland to cropland. We classified primary forest as forest that had not previously been cleared and used for other land uses. The conversion of cropland or grassland to forest includes naturally generated and intentionally planted forest. Cropland is land used for growing agricultural crops and may include short pasture phases, and grassland is land used continuously for grazing purposes, but may include occasional and repeated pasture-renewal phases. While we tried to make categorical distinctions between these land-use types, land uses are often more fluid in practice, which may not always have been stated in the publications underlying our data compilation. When a paper reported both contents and stocks, we used the stock-based measure. We used reported stocks if the original work had already been corrected to equivalent soil mass (Ellert and Bettany, 1995) or if corrected stocks had been reported in previous reviews or meta-analyses (Don et al., 2011; Poeplau et al., 2011; Guo and Gifford, 2002). Where bulk-density correction had not been applied, we tried to make those corrections to estimate changes to equivalent soil mass if studies provided sufficient information on soil bulk density and depth, using the method of Zhang et al. (2004). If that was not possible, we used the reported SOC, TN, or TP contents. Acknowledgements We thank scientists who measured, analyzed, and published the data compiled for this study. We are especially grateful to Drs. Axel Don, Christopher Poeplau, Lex Bouwman, and Gaihe Yang, who provided their global meta-data through personal communication. D.-G.K. acknowledges support from the IAEA CRP D15020. M.U.F.K and L.L.L. were supported by the Strategic Science Investment Fund (SSIF) of New Zealand\u2019s Ministry of Business, Innovation and Employment.", "keywords": ["2. Zero hunger", "13. Climate action", "land-use change", " greenhouse gas emissions", " soil", " carbon", " nitrogen", " phosphorus", " stoichiometry", " time", " temperature", " rainfall", " forest type", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7656722"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7656722", "name": "item", "description": "10.5281/zenodo.7656722", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7656722"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-02-20T00:00:00Z"}}, {"id": "10773/25427", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:26Z", "type": "Journal Article", "created": "2018-01-07", "title": "Toxicokinetics of Zn and Cd in the earthworm Eisenia andrei exposed to metal-contaminated soils under different combinations of air temperature and soil moisture content", "description": "This study evaluated how different combinations of air temperature (20\u202f\u00b0C and 25\u202f\u00b0C) and soil moisture content (50% and 30% of the soil water holding capacity, WHC), reflecting realistic climate change scenarios, affect the bioaccumulation kinetics of Zn and Cd in the earthworm Eisenia andrei. Earthworms were exposed for 21\u202fd to two metal-contaminated soils (uptake phase), followed by 21\u202fd incubation in non-contaminated soil (elimination phase). Body Zn and Cd concentrations were checked in time and metal uptake (k1) and elimination (k2) rate constants determined; metal bioaccumulation factor (BAF) was calculated as k1/k2. Earthworms showed extremely fast uptake and elimination of Zn, regardless of the exposure level. Climate conditions had no major impacts on the bioaccumulation kinetics of Zn, although a tendency towards lower k1 and k2 values was observed at 25\u00a0\u00b0C\u00a0+\u00a030% WHC. Earthworm Cd concentrations gradually increased with time upon exposure to metal-contaminated soils, especially at 50% WHC, and remained constant or slowly decreased following transfer to non-contaminated soil. Different combinations of air temperature and soil moisture content changed the bioaccumulation kinetics of Cd, leading to higher k1 and k2 values for earthworms incubated at 25\u00a0\u00b0C\u00a0+\u00a050% WHC and slower Cd kinetics at 25\u00a0\u00b0C\u00a0+\u00a030% WHC. This resulted in greater BAFs for Cd at warmer and drier environments which could imply higher toxicity risks but also of transfer of Cd within the food chain under the current global warming perspective.", "keywords": ["Soil invertebrates", "Bioavailability", "Climate Change", "0211 other engineering and technologies", "02 engineering and technology", "Global Warming", "01 natural sciences", "Soil", "Metals", " Heavy", "SDG 13 - Climate Action", "Climate change", "Animals", "Soil Pollutants", "Oligochaeta", "0105 earth and related environmental sciences", "2. Zero hunger", "Triazines", "Temperature", "Water", "Bioaccumulation", "Mining wastes", "Toxicokinetics", "Zinc", "Heavy metals", "Metals", "13. Climate action", "Environmental Pollution", "Cadmium"]}, "links": [{"href": "https://doi.org/10773/25427"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Chemosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10773/25427", "name": "item", "description": "10773/25427", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10773/25427"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-04-01T00:00:00Z"}}, {"id": "1295b9994deae0387c2be67c1d753988", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:36Z", "type": "Report", "title": "Global maps of soil temperature", "description": "Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0\u20135 and 5\u201315 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\u00b0C (mean = 3.0 \u00b1 2.1\u00b0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 \u00b1 2.3\u00b0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (\u22120.7 \u00b1 2.3\u00b0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.", "keywords": ["near-surface temperatures", "bioclimatic variables", "soil temperature", "temperature offset", "global maps", "soil-dwelling organisms", "weather stations", "microclimate", "Climate Science", "Klimatvetenskap"], "contacts": [{"organization": "Lembrechts, Jonas J., van den Hoogen, Johan, Dorrepaal, Ellen, Larson, Keith, Sarneel, Judith M., Walz, Josefine, Nijs, Ivan, Lenoir, Jonathan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/1295b9994deae0387c2be67c1d753988"}, {"rel": "self", "type": "application/geo+json", "title": "1295b9994deae0387c2be67c1d753988", "name": "item", "description": "1295b9994deae0387c2be67c1d753988", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1295b9994deae0387c2be67c1d753988"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:40Z", "type": "Journal Article", "created": "2024-03-21", "title": "Environmental drivers and remote sensing proxies of post-fire thaw depth in Eastern Siberian larch forests", "description": "

Abstract. Boreal fire regimes are intensifying because of climate change and the northern parts of boreal forests are underlain by permafrost. Boreal fires combust vegetation and organic soils, which insulate permafrost, and as such deepen the seasonally thawed active layer and can lead to further carbon emissions to the atmosphere. Current understanding of the environmental drivers of post-fire thaw depth is limited but of critical importance. In addition, mapping thaw depth over fire scars may enable a better understanding of the spatial variability in post-fire responses of permafrost soils. We assessed the environmental drivers of post-fire thaw depth using field data from a fire scar in a larch-dominated forest in the continuous permafrost zone in Eastern Siberia. Particularly, summer thaw depth was deeper in burned (mean = 127.3 cm, standard deviation (sd) = 27.7 cm) than in unburned (98.1 cm, sd = 26.9 cm) landscapes one year after the fire, yet the effect of fire was modulated by landscape and vegetation characteristics. We found deeper thaw in well-drained landscape positions, in open larch forest often intermixed with Scots pine, and in high severity burns. The environmental drivers, site moisture, forest type and density, and fire severity explained 73.4 % of the measured thaw depth variability at the study sites. In addition, we evaluated the relationships between field-measured thaw depth and several remote sensing proxies. Albedo, the differenced Normalized Burn Ratio (dNBR), land surface temperature (LST), and pre-fire Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 imagery together explained 66.3 % of the variability in field-measured thaw depth. Based on these remote sensing proxies and multiple linear regression analysis, we estimated thaw depth over the entire fire scar, and found that LST displayed particularly strong correlations with post-fire thaw depth (r = 0.65, p < 0.01). Our study reveals some of the governing processes of post-fire thaw depth development and shows the capability of Landsat imagery to estimate thaw depth at a landscape scale.

", "keywords": ["Dynamic and structural geology", "QE1-996.5", "13. Climate action", "Science", "Q", "Geology", "QE500-639.5", "Deforestation", "15. Life on land", "Landsat", "Multiple linear regression", "Atmospheric temperature"]}, "links": [{"href": "https://esd.copernicus.org/articles/15/1459/2024/esd-15-1459-2024.pdf"}, {"href": "https://doi.org/1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Dynamics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a", "name": "item", "description": "1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-21T00:00:00Z"}}, {"id": "10.1002/2017JD027346", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:28Z", "type": "Journal Article", "created": "2017-12-28", "title": "Soil Moisture-Temperature Coupling in a Set of Land Surface Models", "description": "Abstract

The land surface controls the partitioning of water and energy fluxes and therefore plays a crucial role in the climate system. The coupling between soil moisture and air temperature, in particular, has been shown to affect the severity and occurrence of temperature extremes and heat waves. Here we study soil moisture\uffe2\uff80\uff90temperature coupling in five land surface models, focusing on the terrestrial segment of the coupling in the warm season. All models are run off\uffe2\uff80\uff90line over a common period with identical atmospheric forcing data, in order to allow differences in the results to be attributed to the models' partitioning of energy and water fluxes. Coupling is calculated according to two semiempirical metrics, and results are compared to observational flux tower data. Results show that the locations of the global hot spots of soil moisture\uffe2\uff80\uff90temperature coupling are similar across all models and for both metrics. In agreement with previous studies, these areas are located in transitional climate regimes. The magnitude and local patterns of model coupling, however, can vary considerably. Model coupling fields are compared to tower data, bearing in mind the limitations in the geographical distribution of flux towers and the differences in representative area of models and in situ data. Nevertheless, model coupling correlates in space with the tower\uffe2\uff80\uff90based results (r = 0.5\uffe2\uff80\uff930.7), with the multimodel mean performing similarly to the best\uffe2\uff80\uff90performing model. Intermodel differences are also found in the evaporative fractions and may relate to errors in model parameterizations and ancillary data of soil and vegetation characteristics.

", "keywords": ["ENVIRONMENT SIMULATOR JULES", "FLUXES", "0207 environmental engineering", "02 engineering and technology", "01 natural sciences", "CO2 EXCHANGE", "models", "WATER", "SCALE", "Research Articles", "0105 earth and related environmental sciences", "land surface", "CARBON-DIOXIDE EXCHANGE", "eartH2Observe", "temperature", "15. Life on land", "DECIDUOUS FOREST", "CLIMATE", "EVAPORATION", "VARIABILITY", "13. Climate action", "Earth and Environmental Sciences", "BALANCE", "land surface models", "SENSIBLE HEAT", "land-atmosphere interactions", "soil moisture"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017JD027346"}, {"href": "https://doi.org/10.1002/2017JD027346"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Geophysical%20Research%3A%20Atmospheres", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/2017JD027346", "name": "item", "description": "10.1002/2017JD027346", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2017JD027346"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-02-01T00:00:00Z"}}, {"id": "10.1111/gcb.13013", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:18:00Z", "type": "Journal Article", "created": "2015-06-27", "title": "Canopy Warming Caused Photosynthetic Acclimation And Reduced Seed Yield In Maize Grown At Ambient And Elevated [Co2]", "description": "Abstract

Rising atmosphericCO2concentration ([CO2]) and attendant increases in growing season temperature are expected to be the most important global change factors impacting production agriculture. Although maize is the most highly produced crop worldwide, few studies have evaluated the interactive effects of elevated [CO2] and temperature on its photosynthetic physiology, agronomic traits or biomass, and seed yield under open field conditions. This study investigates the effects of rising [CO2] and warmer temperature, independently and in combination, on maize grown in the field throughout a full growing season. Free\uffe2\uff80\uff90airCO2enrichment (FACE) technology was used to target atmospheric [CO2] to 200\uffc2\uffa0\uffce\uffbcmol\uffc2\uffa0mol\uffe2\uff88\uff921above ambient [CO2] and infrared heaters to target a plant canopy increase of 3.5\uffc2\uffa0\uffc2\uffb0C, with actual season mean heating of ~2.7\uffc2\uffa0\uffc2\uffb0C, mimicking conditions predicted by the second half of this century. Photosynthetic gas\uffe2\uff80\uff90exchange parameters, leaf nitrogen and carbon content, leaf water potential components, and developmental measurements were collected throughout the season, and biomass and yield were measured at the end of the growing season. As predicted for a C4plant, elevated [CO2] did not stimulate photosynthesis, biomass, or yield. Canopy warming caused a large shift in aboveground allocation by stimulating season\uffe2\uff80\uff90long vegetative biomass and decreasing reproductive biomass accumulation at bothCO2concentrations, resulting in decreased harvest index. Warming caused a reduction in photosynthesis due to down\uffe2\uff80\uff90regulation of photosynthetic biochemical parameters and the decrease in the electron transport rate. The reduction in seed yield with warming was driven by reduced photosynthetic capacity and by a shift in aboveground carbon allocation away from reproduction. This field study portends that future warming will reduce yield in maize, and this will not be mitigated by higher atmospheric [CO2] unless appropriate adaptation traits can be introduced into future cultivars.

", "keywords": ["0301 basic medicine", "2. Zero hunger", "03 medical and health sciences", "Hot Temperature", "13. Climate action", "Acclimatization", "Seeds", "Illinois", "Carbon Dioxide", "Photosynthesis", "15. Life on land", "Zea mays"]}, "links": [{"href": "https://doi.org/10.1111/gcb.13013"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcb.13013", "name": "item", "description": "10.1111/gcb.13013", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcb.13013"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-09-23T00:00:00Z"}}, {"id": "10.1016/j.chemosphere.2013.12.024", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:51Z", "type": "Journal Article", "created": "2014-01-04", "title": "Carbon Mineralization In Two Ultisols Amended With Different Sources And Particle Sizes Of Pyrolyzed Biochar", "description": "Biochar produced during pyrolysis has the potential to enhance soil fertility and reduce greenhouse gas emissions. The influence of biochar properties (e.g., particle size) on both short- and long-term carbon (C) mineralization of biochar remains unclear. There is minimal information on the potential effects of biochar particle sizes on their breakdowns by soil microorganism, so it is unknown if the particle size of biochar influences C mineralization rate and/or stability in soils. In order to evaluate the effect of different sources (BS) and particle sizes (BF) of biochar on C loss and/or stability in soils, an incubation study on C mineralization of different biochar sources and particle sizes was established using two soils (ST): Norfolk soil (fine loamy, kaolinitic, thermic, typic Kandiudults) and Coxville soil (fine loamy kaolinitic, thermic, Paleaquults). In separate incubation vessels, these soils were amended with one of two manure-based biochars (poultry litters, PL; swine solids, SS) or one of two lignocellulosic-based biochars (switchgrass, SG; pine chips, PC) which were processed into two particle sizes (dust, <0.42 mm; pellet, >2 mm). The amount of CO2 evolved varied significantly between soils (p\u22640.0001); particle sizes (p\u22640.0001) and the interactions of biochar source (p\u22640.001) and forms of biochars (p\u22640.0001) with soil types. Averaged across soils and sources of biochar, CO2-C evolved from dust-sized biochar (281 mg kg(-1)) was significantly higher than pellet-sized biochar (226 mg kg(-1)). Coxville soils with SS biochar produced the greatest average CO2-C of 428 mg kg(-1) and Norfolk soils with PC had the lowest CO2-C production (93 mg kg(-1)). Measured rates of carbon mineralization also varied with soils and sources of biochar (Norfolk: PL>SS>SG\u2265PC; Coxville: PC>SG>SS>PL). The average net CO2-C evolved from the Coxville soils (385 mg kg(-1)) was about threefold more than the CO2-C evolved from the Norfolk soils (123 mg kg(-1)). Our results suggest different particle sizes and sources of biochar as well as soil type influence biochar stability.", "keywords": ["2. Zero hunger", "Minerals", "Hot Temperature", "Swine", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "Carbon", "Poultry", "6. Clean water", "Manure", "Soil", "13. Climate action", "Charcoal", "11. Sustainability", "Animals", "0401 agriculture", " forestry", " and fisheries", "Particle Size", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.chemosphere.2013.12.024"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Chemosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.chemosphere.2013.12.024", "name": "item", "description": "10.1016/j.chemosphere.2013.12.024", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.chemosphere.2013.12.024"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-05-01T00:00:00Z"}}, {"id": "10.3390/genes15010107", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:19:39Z", "type": "Journal Article", "created": "2024-01-16", "title": "Structural and Functional Shifts in the Microbial Community of a Heavy Metal-Contaminated Soil Exposed to Short-Term Changes in Air Temperature, Soil Moisture and UV Radiation", "description": "

The interplay between metal contamination and climate change may exacerbate the negative impact on the soil microbiome and, consequently, on soil health and ecosystem services. We assessed the response of the microbial community of a heavy metal-contaminated soil when exposed to short-term (48 h) variations in air temperature, soil humidity or ultraviolet (UV) radiation in the absence and presence of Enchytraeus crypticus (soil invertebrate). Each of the climate scenarios simulated significantly altered at least one of the microbial parameters measured. Irrespective of the presence or absence of invertebrates, the effects were particularly marked upon exposure to increased air temperature and alterations in soil moisture levels (drought and flood scenarios). The observed effects can be partly explained by significant alterations in soil properties such as pH, dissolved organic carbon, and water-extractable heavy metals, which were observed for all scenarios in comparison to standard conditions. The occurrence of invertebrates mitigated some of the impacts observed on the soil microbial community, particularly in bacterial abundance, richness, diversity, and metabolic activity. Our findings emphasize the importance of considering the interplay between climate change, anthropogenic pressures, and soil biotic components to assess the impact of climate change on terrestrial ecosystems and to develop and implement effective management strategies.

", "keywords": ["0301 basic medicine", "2. Zero hunger", "Soil invertebrates", "Soil microbiome", "Soil drought", "Ultraviolet Rays", "Soil pollution", "Microbiota", "Temperature", "Enchytraeus crypticus", "15. Life on land", "01 natural sciences", "Article", "6. Clean water", "Soil", "03 medical and health sciences", "13. Climate action", "UVR exposure", "Metals", " Heavy", "Climate change", "Soil flood", "Metagenomics", "Increased temperature", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.3390/genes15010107"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Genes", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/genes15010107", "name": "item", "description": "10.3390/genes15010107", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/genes15010107"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-16T00:00:00Z"}}, {"id": "97989154d4be17f52279916f311b52e3", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:24:36Z", "type": "Report", "title": "Characterization and Modeling of SiC Integrated Circuits for Harsh Environment", "description": "Elektronik f\u00f6r extrema milj\u00f6er, som kan anv\u00e4ndas vid h\u00f6g temperatur, h\u00f6g\u00a0str\u00e5lning och omgivning med fr\u00e4tande gaser, har varit starkt \u00f6nskv\u00e4rd vid utforskning av rymden och \u00f6vervakning av k\u00e4rnreaktorer. Kiselkarbid (SiC) \u00e4r en av kandidaterna inom material f\u00f6r extrema milj\u00f6er p\u00e5 grund av sin h\u00f6ga temperatur- och h\u00f6ga str\u00e5lnings-tolerans. Syftet med denna avhandling \u00e4r att karakterisera 4H-SiC MOSFETar vid h\u00f6g temperatur och att konstruera SPICE modeller f\u00f6r 4H-SiC MOSFETar. MOSFET-transistorer karakteriserades till 500\u00b0C. Med anv\u00e4ndande av karakt\u00e4ristik f\u00f6r en 4H-SiC NMOSFET med L/W = 10 \u00b5m / 50 \u00b5m, anpassades en SPICE LEVEL 2 kretsmodell. Modellen beskriver DC karakteristiska av 4H- SiC MOSFETar mellan 25\u00baC och 450\u00baC. Baserat p\u00e5 SPICE-kretsmodellen simulerades egenskaper f\u00f6r operationsf\u00f6rst\u00e4rkare och digitala inverterar. D\u00e4rut\u00f6ver analyserades driften av pseudo-CMOS vid h\u00f6g temperatur och principen f\u00f6r konstruktion av pseudo-CMOS f\u00f6reslogs. Arean och utbytet (s.k. yield) av pseudo-CMOS integrerade kretsar uppskattades och det visar sig att SiC pseudo-CMOS integrerade kretsar kan anv\u00e4nda mindre area \u00e4n SiC CMOS integrerade kretsar. Harsh environment electronics, which can be operated at high-temperature, high-radiation, and corrosive gas environment, has been strongly desired in space exploration and monitoring of nuclear reactors. Silicon Carbide (SiC) is one of the candidates of materials for harsh environment electronics because of its high-temperature and high-radiation tolerance.\u200c The objective of this thesis is to characterize 4H-SiC MOSFETs at high- temperature and to construct SPICE models of the 4H-SiC MOSFETs. The MOSFET devices were characterized up to 500\u00baC. Using the characteristic of a 4H-SiC NMOSFET with\u00a0L/W\u00a0= 10 \u00b5m/50 \u00b5m, a SPICE LEVEL 2 circuit model was constructed. This model describes the DC characteristic of the 4H-SiC MOSFETs in the range of 25 \u2013 450\u00baC. Based on the SPICE circuit model, the characteristics of operational amplifiers and digital inverters were simulated. Furthermore, the operation of pseudo-CMOS at high-temperature was analyzed and the operation principle of pseudo-CMOS was suggested. The device area and yield of pseudo-CMOS integrated circuits were estimated and it is shown that SiC pseudo-CMOS integrated circuits can use less area than SiC CMOS integrated circuits.", "keywords": ["Computer and Information Sciences", "Extrema Milj\u00f6er", "SPICE circuit simulation", "Data- och informationsvetenskap", "Silicon carbide", "High-temperature", "H\u00f6g tempeatur", "Electrical Engineering", " Electronic Engineering", " Information Engineering", "Yield calculation", "Utbytet utr\u00e4kning", "Harsh environment", "Pseudo-CMOS", "Elektroteknik och elektronik", "SPICE kretssimulering"], "contacts": [{"organization": "Kimoto, Daiki", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/97989154d4be17f52279916f311b52e3"}, {"rel": "self", "type": "application/geo+json", "title": "97989154d4be17f52279916f311b52e3", "name": "item", "description": "97989154d4be17f52279916f311b52e3", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/97989154d4be17f52279916f311b52e3"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-01-01T00:00:00Z"}}, {"id": "10.1007/s00248-007-9295-1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:44Z", "type": "Journal Article", "created": "2007-08-31", "title": "Plfa Profiling Of Microbial Community Structure And Seasonal Shifts In Soils Of A Douglas-Fir Chronosequence", "description": "The impact and frequency of forest harvesting could significantly affect soil microbial community (SMC) structure and functioning. The ability of soil microorganisms to perform biogeochemical processes is critical for sustaining forest productivity and has a direct impact on decomposition dynamics and carbon storage potential. The Wind River Canopy Crane Research Forest in SW, WA, provided a unique opportunity to study a forest chronosequence and the residual effects of harvesting on the SMC in comparison to old-growth forests. The objective of this study was to determine the effect of clear-cutting and stand age on temporal dynamics of SMC and physiological stress markers using phospholipid fatty acid (PLFA) profiling. Soil microbial PLFA profiles were determined seven times over 22 months (Nov. 02 to Sep. 04) in old-growth coniferous forest stands (300-500 years) and 8 (CC8)- or 25 (CC25)-year-old replanted clear-cuts. PLFA patterns of the SMC shifted because of clear-cutting, but seasonal temporal changes had greater shifts than differences among stand age. The microbial biomass (total PLFA) and bacterial, fungal, and selected other PLFAs were significantly reduced in CC8 but not in CC25 sites relative to the old-growth sites. An increase in stress indicators [PLFA ratios of saturated/monsaturated and (cy17:0 + cy19:0)/(16:1omega7 + 18:1omega7)] in late summer was related to water stress. Although the canopy and litter input are quite different for a 25-year clear-cut compared to virgin old-growth forest, we conclude that the composition of the microbial communities, 25 years after clear-cutting, has recovered sufficiently to be much more similar to old-growth forests than a recent clear-cut at this Pacific Northwest forest site. The study shows the potential of PLFA analysis for profiling microbial communities and their stress status under field conditions, but wide temporal shifts emphasize the need for sampling over seasons to fully interpret ecosystem management impacts on microbial populations.", "keywords": ["Washington", "Time Factors", "Bacteria", "Fatty Acids", "Fungi", "Temperature", "Eukaryota", "Water", "04 agricultural and veterinary sciences", "15. Life on land", "Pseudotsuga", "Trees", "Soil", "13. Climate action", "Animals", "0401 agriculture", " forestry", " and fisheries", "Biomass", "Seasons", "Phospholipids", "Soil Microbiology"]}, "links": [{"href": "https://doi.org/10.1007/s00248-007-9295-1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Microbial%20Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00248-007-9295-1", "name": "item", "description": "10.1007/s00248-007-9295-1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00248-007-9295-1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2007-08-31T00:00:00Z"}}, {"id": "012ce7af-7212-41e1-96da-a38fbd32fd7c", "type": "Feature", "geometry": null, "properties": {"updated": "2025-08-09T09:20:29.683803", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-08-09 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-08-09 ore 00 UTC - Valido dalle ore 00 UTC del 2025-08-09 alle ore 00 UTC del 2025-08-12. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-08-09", "20250809t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-08-09-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/012ce7af-7212-41e1-96da-a38fbd32fd7c"}, {"rel": "self", "type": "application/geo+json", "title": "012ce7af-7212-41e1-96da-a38fbd32fd7c", "name": "item", "description": "012ce7af-7212-41e1-96da-a38fbd32fd7c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/012ce7af-7212-41e1-96da-a38fbd32fd7c"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "oai:serval.unil.ch:BIB_38E93A02220B", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:28:36Z", "type": "Report", "title": "Global maps of soil temperature.", "description": "Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km <sup>2</sup> resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km <sup>2</sup> pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\u00b0C (mean = 3.0 \u00b1 2.1\u00b0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 \u00b1 2.3\u00b0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 \u00b1 2.3\u00b0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.", "keywords": ["Climate Change; Ecosystem; Microclimate; Soil; Temperature; bioclimatic variables; global maps; microclimate; near-surface temperatures; soil temperature; soil-dwelling organisms; temperature offset; weather stations"], "contacts": [{"organization": "Lembrechts, J.J., van den Hoogen, J., Aalto, J., Ashcroft, M.B., De Frenne, P., Kemppinen, J., Kopeck\u00fd, M., Luoto, M., Maclean, IMD, Crowther, T.W., Bailey, J.J., Haesen, S., Klinges, D.H., Niittynen, P., Scheffers, B.R., Van Meerbeek, K., Aartsma, P., Abdalaze, O., Abedi, M., Aerts, R., Ahmadian, N., Ahrends, A., Alatalo, J.M., Alexander, J.M., Allonsius, C.N., Altman, J., Ammann, C., Andres, C., Andrews, C., Ard\u00f6, J., Arriga, N., Arzac, A., Aschero, V., Assis, R.L., Assmann, J.J., Bader, M.Y., Bahalkeh, K., Baran\u010dok, P., Barrio, I.C., Barros, A., Barthel, M., Basham, E.W., Bauters, M., Bazzichetto, M., Marchesini, L.B., Bell, M.C., Benavides, J.C., Benito Alonso, J.L., Berauer, B.J., Bjerke, J.W., Bj\u00f6rk, R.G., Bj\u00f6rkman, M.P., Bj\u00f6rnsd\u00f3ttir, K., Blonder, B., Boeckx, P., Boike, J., Bokhorst, S., Brum, BNS, Br\u016fna, J., Buchmann, N., Buysse, P., Camargo, J.L., Campoe, O.C., Candan, O., Canessa, R., Cannone, N., Carbognani, M., Carnicer, J., Casanova-Katny, A., Cesarz, S., Chojnicki, B., Choler, P., Chown, S.L., Cifuentes, E.F., \u010ciliak, M., Contador, T., Convey, P., Cooper, E.J., Cremonese, E., Curasi, S.R., Curtis, R., Cutini, M., Dahlberg, C.J., Daskalova, G.N., de Pablo, M.A., Della Chiesa, S., Dengler, J., Deronde, B., Descombes, P., Di Cecco, V., Di Musciano, M., Dick, J., Dimarco, R.D., Dolezal, J., Dorrepaal, E., Du\u0161ek, J., Eisenhauer, N., Eklundh, L., Erickson, T.E., Erschbamer, B., Eugster, W., Ewers, R.M., Exton, D.A., Fanin, N., Fazlioglu, F., Feigenwinter, I., Fenu, G., Ferlian, O., Fern\u00e1ndez Calzado, M.R., Fern\u00e1ndez-Pascual, E., Finckh, M., Higgens, R.F., Forte, TGW, Freeman, E.C., Frei, E.R., Fuentes-Lillo, E., Garc\u00eda, R.A., Garc\u00eda, M.B., G\u00e9ron, C., Gharun, M., Ghosn, D., Gigauri, K., Gobin, A., Goded, I., Goeckede, M., Gottschall, F., Goulding, K., Govaert, S., Graae, B.J., Greenwood, S., Greiser, C., Grelle, A., Gu\u00e9nard, B., Guglielmin, M., Guillemot, J., Haase, P., Haider, S., Halbritter, A.H., Hamid, M., Hammerle, A., Hampe, A., Haugum, S.V., Hederov\u00e1, L., Heinesch, B., Helfter, C., Hepenstrick, D., Herberich, M., Herbst, M., Hermanutz, L., Hik, D.S., Hoffr\u00e9n, R., Homeier, J., H\u00f6rtnagl, L., H\u00f8ye, T.T., Hrbacek, F., Hylander, K., Iwata, H., Jackowicz-Korczynski, M.A., Jactel, H., J\u00e4rveoja, J., Jastrz\u0119bowski, S., Jentsch, A., Jim\u00e9nez, J.J., J\u00f3nsd\u00f3ttir, I.S., Jucker, T., Jump, A.S., Juszczak, R., Kanka, R., Ka\u0161par, V., Kazakis, G., Kelly, J., Khuroo, A.A., Klemedtsson, L., Klisz, M., Kljun, N., Knohl, A., Kobler, J., Koll\u00e1r, J., Kotowska, M.M., Kov\u00e1cs, B., Kreyling, J., Lamprecht, A., Lang, S.I., Larson, C., Larson, K., Laska, K., le Maire, G., Leihy, R.I., Lens, L., Liljebladh, B., Lohila, A., Lorite, J., Loubet, B., Lynn, J., Macek, M., Mackenzie, R., Magliulo, E., Maier, R., Malfasi, F., M\u00e1li\u0161, F.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/oai:serval.unil.ch:BIB_38E93A02220B"}, {"rel": "self", "type": "application/geo+json", "title": "oai:serval.unil.ch:BIB_38E93A02220B", "name": "item", "description": "oai:serval.unil.ch:BIB_38E93A02220B", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/oai:serval.unil.ch:BIB_38E93A02220B"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-01T00:00:00Z"}}, {"id": "0233df11-412c-4c84-a9b2-7eb9dc3409d4", "type": "Feature", "geometry": null, "properties": {"updated": "2025-04-30T11:21:35.673675Z", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-04-30 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-04-30 ore 00 UTC - Valido dalle ore 00 UTC del 2025-04-30 alle ore 00 UTC del 2025-05-03. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-04-30", "20250430t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-04-30-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/0233df11-412c-4c84-a9b2-7eb9dc3409d4"}, {"rel": "self", "type": "application/geo+json", "title": "0233df11-412c-4c84-a9b2-7eb9dc3409d4", "name": "item", "description": "0233df11-412c-4c84-a9b2-7eb9dc3409d4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0233df11-412c-4c84-a9b2-7eb9dc3409d4"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "10.1016/j.agrformet.2018.04.010", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:35Z", "type": "Journal Article", "created": "2018-04-19", "title": "A phenomenological model of soil evaporative efficiency using surface soil moisture and temperature data", "description": "Abstract Modeling soil evaporation has been a notorious challenge due to the complexity of the phenomenon and the lack of data to constrain it. In this context, a parsimonious model is developed to estimate soil evaporative efficiency (SEE) defined as the ratio of actual to potential soil evaporation. It uses a soil resistance driven by surface (0\u20135\u202fcm) soil moisture, meteorological forcing and time (hour) of day, and has the capability to be calibrated using the radiometric surface temperature derived from remotely sensed thermal data. The new approach is tested over a rainfed semi-arid site, which had been under bare soil conditions during a 9-month period in 2016. Three calibration strategies are adopted based on SEE time series derived from (1) eddy-covariance measurements, (2) thermal measurements, and (3) eddy-covariance measurements used only over separate drying periods between significant rainfall events. The correlation coefficients (and slopes of the linear regression) between simulated and observed (eddy-covariance-derived) SEE are 0.85, 0.86 and 0.87 (and 0.91, 0.87 and 0.91) for calibration strategies 1, 2 and 3, respectively. Moreover, the correlation coefficient (and slope of the linear regression) between simulated and observed SEE is improved from 0.80 to 0.85 (from 0.86 to 0.91) when including hour of day in the soil resistance. The reason is that, under non-energy-limited conditions, the receding evaporation front during daytime makes SEE decrease at the hourly time scale. The soil resistance formulation can be integrated into state-of-the-art dual-source surface models and has calibration capabilities across a range of spatial scales from spaceborne microwave and thermal data.", "keywords": ["550", "0207 environmental engineering", "Soil resistance", "02 engineering and technology", "Remote sensing", "15. Life on land", "calibration", "surface temperature", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Surface temperature", "remote sensing", "Calibration", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "soil resistance", "Soil moisture", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "soil moisture", "environment", "Soil evaporation"]}, "links": [{"href": "https://doi.org/10.1016/j.agrformet.2018.04.010"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20and%20Forest%20Meteorology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agrformet.2018.04.010", "name": "item", "description": "10.1016/j.agrformet.2018.04.010", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agrformet.2018.04.010"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-06-01T00:00:00Z"}}, {"id": "10.1016/j.agwat.2021.107290", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:37Z", "type": "Journal Article", "created": "2021-11-22", "title": "Assimilation of SMAP disaggregated soil moisture and Landsat land surface temperature to improve FAO-56 estimates of ET in semi-arid regions", "description": "Accurate estimation of evapotranspiration (ET) is of crucial importance in water science and hydrological process understanding especially in semi-arid/arid areas since ET represents more than 85% of the total water budget. FAO-56 is one of the widely used formulations to estimate the actual crop evapotranspiration (ET c act) due to its operational nature and since it represents a reasonable compromise between simplicity and accuracy. In this vein, the objective of this paper was to examine the possibility of improving ET c act estimates through remote sensing data assimilation. For this purpose, remotely sensed soil moisture (SM) and Land surface temperature (LST) data were simultaneously assimilated into FAO-dualK c. Surface SM observations were assimilated into the soil evaporation (E s) component through the soil evaporation coefficient, and LST data were assimilated into the actual crop transpiration (T c act) component through the crop stress coefficient. The LST data were used to estimate the water stress coefficient (K s) as a proxy of LST (LST proxy). The FAO-Ks was corrected by assimilating LST proxy derived from Landsat data based on the variances of predicted errors on K s estimates from FAO-56 model and thermal-derived K s. The proposed approach was tested over a semi-arid area in Morocco using first, in situ data collected during 2002-2003 and 2015-2016 wheat growth seasons over two different fields and then, remotely sensed data derived from disaggregated Soil Moisture Active Passive (SMAP) SM and Landsat-LST sensors were used. Assimilating SM data leads to an improvement of the ET c act model prediction: the root mean square error (RMSE) decreased from 0.98 to 0.65 mm/day compared to the classical FAO-dualK c using in situ SM. Moreover, assimilating both in situ SM and LST data provided more accurate results with a RMSE error of 0.55 mm/day. By using SMAP-based SM and Landsat-LST, results also improved in comparison with standard FAO and reached a RMSE of 0.73 mm/day against eddy-covariance ET c act measurements.", "keywords": ["2. Zero hunger", "0106 biological sciences", "Evapotranspiration", "550", "Evapotranspiration Data assimilation FAO-dualK c Soil moisture Land surface temperature", "0207 environmental engineering", "02 engineering and technology", "15. Life on land", "01 natural sciences", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "FAO-dualK(c)", "13. Climate action", "Data assimilation", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Soil moisture", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Land surface temperature"]}, "links": [{"href": "https://doi.org/10.1016/j.agwat.2021.107290"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20Water%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agwat.2021.107290", "name": "item", "description": "10.1016/j.agwat.2021.107290", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agwat.2021.107290"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-01T00:00:00Z"}}, {"id": "0411b9a3-3406-4e72-bceb-a9a13cb8db4c", "type": "Feature", "geometry": null, "properties": {"updated": "2025-09-18T11:24:25.243396", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-09-18 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-09-18 ore 00 UTC - Valido dalle ore 00 UTC del 2025-09-18 alle ore 00 UTC del 2025-09-21. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-09-18", "20250918t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-09-18-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250918T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250918T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250918T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250918T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250918T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250918T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250918T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250918T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/0411b9a3-3406-4e72-bceb-a9a13cb8db4c"}, {"rel": "self", "type": "application/geo+json", "title": "0411b9a3-3406-4e72-bceb-a9a13cb8db4c", "name": "item", "description": "0411b9a3-3406-4e72-bceb-a9a13cb8db4c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0411b9a3-3406-4e72-bceb-a9a13cb8db4c"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "10.1016/j.agwat.2017.08.007", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:37Z", "type": "Journal Article", "created": "2017-08-10", "title": "Performance of the two-source energy budget (TSEB) model for the monitoring of evapotranspiration over irrigated annual crops in North Africa", "description": "Abstract The main objective of this study was to evaluate the performance and the domain of validity of the two-source energy balance model (TSEB) for the monitoring of actual evapotranspiration ( ET a ) as a first step towards its use for irrigation planning. Secondary objectives were to analyze the ability of TSEB model to detect water stress and to evaluate evapotranspiration partition between evaporation (E) and transpiration (T) over irrigated annual crops. Within this context, TSEB was compared to the calibrated FAO-56 dual approach, taken as a reference tool for the monitoring of crop water consumption. TSEB computes ET a as the residual of a double component energy balance driven by the radiative surface temperature ( T s ) used as a proxy of crop hydric conditions; the FAO-56 dual crop coefficient approach uses the Normalized Difference Vegetation Index (NDVI) as a proxy of Basal Crop Coefficient ( K cb ) and assesses the hydric status directly by solving a two layer soil water budget. Both approaches were evaluated over four plots of wheat and sugar beet located in the Haouz plain (Marrakech, Morocco) that were instrumented with eddy covariance systems during the 2012 and 2013 growing seasons. Series of ASTER images were acquired during the first agricultural season. Both models offered fair performances compared to ET a observations with Root Mean Square Error (RMSE) lower than 1\u00a0mm\u00a0day \u22121 apart from the FAO-56 dual approach on the sugar beet plot because of uncertain irrigation inputs. This highlights a major weakness of this model when water inputs are uncertain; a very likely case at the plot scale. By contrast, the TSEB model offered smoother performances in all cases. The potentialities of both approaches to predict a water stress index based on the departure from potential evapotranspiration ( ET c ) was evaluated: although the FAO-56 dual was better suited to detect high water stresses, the TSEB model was able to detect moderate stresses without a need to prescribe water inputs. Finally, the partition of ET a between soil evaporation and plant transpiration was estimated indirectly by confrontation between simulated soil evaporation and surface (0\u20135\u00a0cm) soil moisture acquired spatially with Theta Probe sensors and taken as a proxy of soil evaporation. TSEB evaporation was well correlated to surface soil moisture (r\u00a0=\u00a00.82) for low Leaf Area Index (LAI) values ( 2 \u00a0m \u22122 ). In addition, TSEB predicted partition compared well to snapshot measurements based on the stable isotope method. This in-depth comparison of two simple tools to monitor ET a leads us to the conclusion that the TSEB model can reasonably be used to map ET a on large scale and possibly for the decision-making process of irrigation scheduling.", "keywords": ["FAO-56", "2. Zero hunger", "550", "Evapotranspiration", "NDVI", "Water stress", "0207 environmental engineering", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "6. Clean water", "Surface temperature", "0401 agriculture", " forestry", " and fisheries", "TSEB"]}, "links": [{"href": "https://doi.org/10.1016/j.agwat.2017.08.007"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20Water%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agwat.2017.08.007", "name": "item", "description": "10.1016/j.agwat.2017.08.007", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agwat.2017.08.007"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-11-01T00:00:00Z"}}, {"id": "06ad1025-911c-4ffb-82de-cda640fbb4fb", "type": "Feature", "geometry": null, "properties": {"updated": "2025-07-10T11:24:00.699488Z", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-07-10 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-07-10 ore 00 UTC - Valido dalle ore 00 UTC del 2025-07-10 alle ore 00 UTC del 2025-07-13. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-07-10", "20250710t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-07-10-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250710T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250710T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250710T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250710T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250710T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250710T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250710T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250710T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/06ad1025-911c-4ffb-82de-cda640fbb4fb"}, {"rel": "self", "type": "application/geo+json", "title": "06ad1025-911c-4ffb-82de-cda640fbb4fb", "name": "item", "description": "06ad1025-911c-4ffb-82de-cda640fbb4fb", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/06ad1025-911c-4ffb-82de-cda640fbb4fb"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "076eb455-c5c5-46ad-88bb-65b73020157e", "type": "Feature", "geometry": null, "properties": {"updated": "2025-07-22T09:20:40.573586", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-07-22 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-07-22 ore 00 UTC - Valido dalle ore 00 UTC del 2025-07-22 alle ore 00 UTC del 2025-07-25. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-07-22", "20250722t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-07-22-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250722T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250722T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250722T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250722T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250722T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250722T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250722T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250722T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/076eb455-c5c5-46ad-88bb-65b73020157e"}, {"rel": "self", "type": "application/geo+json", "title": "076eb455-c5c5-46ad-88bb-65b73020157e", "name": "item", "description": "076eb455-c5c5-46ad-88bb-65b73020157e", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/076eb455-c5c5-46ad-88bb-65b73020157e"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "10.1016/j.soilbio.2011.04.003", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:43Z", "type": "Journal Article", "created": "2011-05-01", "title": "Effects Of Elevated Atmospheric Co2, Prolonged Summer Drought And Temperature Increase On N2o And Ch4 Fluxes In A Temperate Heathland", "description": "Abstract In temperate regions, climate change is predicted to increase annual mean temperature and intensify the duration and frequency of summer droughts, which together with elevated atmospheric carbon dioxide (CO 2 ) concentrations, may affect the exchange of nitrous oxide (N 2 O) and methane (CH 4 ) between terrestrial ecosystems and the atmosphere. We report results from the CLIMAITE experiment, where the effects of these three climate change parameters were investigated solely and in all combinations in a temperate heathland. Field measurements of N 2 O and CH 4 fluxes took place 1\u20132 years after the climate change manipulations were initiated. The soil was generally a net sink for atmospheric CH 4 . Elevated temperature (T) increased the CH 4 uptake by on average 10\u00a0\u03bcg C\u00a0m \u22122 \u00a0h \u22121 , corresponding to a rise in the uptake rate of about 20%. However, during winter elevated CO 2 (CO 2 ) reduced the CH 4 uptake, which outweighed the positive effect of warming when analyzed across the study period. Emissions of N 2 O were generally low ( \u22122 \u00a0h \u22121 ). As single experimental factors, elevated CO 2 , temperature and summer drought (D) had no major effect on the N 2 O fluxes, but the combination of CO 2 and warming (TCO 2 ) stimulated N 2 O emission, whereas the N 2 O emission ceased when CO 2 was combined with drought (DCO 2 ). We suggest that these N 2 O responses are related to increased rhizodeposition under elevated CO 2 combined with increased and reduced nitrogen turnover rates caused by warming and drought, respectively. The N 2 O flux in the multifactor treatment TDCO 2 was not different from the ambient control treatment. Overall, our study suggests that in the future, CH 4 uptake may increase slightly, while N 2 O emission will remain unchanged in temperate ecosystems on well-aerated soils. However, we propose that continued exposure to altered climate could potentially change the greenhouse gas flux pattern in the investigated heathland.", "keywords": ["summer", "FLUXES", "ELEVATED ATMOSPHERIC CO2", "CH4", "CH4 FLUX", "N2O", "temperature", "/dk/atira/pure/sustainabledevelopmentgoals/life_on_land; name=SDG 15 - Life on Land", "drought", "Environment and climate", "04 agricultural and veterinary sciences", "heathland", "15. Life on land", "Milj\u00f8 og klima", "6. Clean water", "flux", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "CO2", "/dk/atira/pure/sustainabledevelopmentgoals/climate_action; name=SDG 13 - Climate Action", "ATMOSPHERIC CO2", "temperate"]}, "links": [{"href": "https://doi.org/10.1016/j.soilbio.2011.04.003"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Biology%20and%20Biochemistry", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.soilbio.2011.04.003", "name": "item", "description": "10.1016/j.soilbio.2011.04.003", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.soilbio.2011.04.003"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-08-01T00:00:00Z"}}, {"id": "0d1800b5-d842-4af3-846c-5d97ae3f0307", "type": "Feature", "geometry": null, "properties": {"updated": "2025-05-31T06:21:11.117921", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-05-30 ore 12 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-05-30 ore 12 UTC - Valido dalle ore 12 UTC del 2025-05-30 alle ore 00 UTC del 2025-06-03. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["120000", "2025-05-30", "20250530t120000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN12/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-05-30-ore-12-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250530T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250530T120000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250530T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250530T120000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250530T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250530T120000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250530T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250530T120000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/0d1800b5-d842-4af3-846c-5d97ae3f0307"}, {"rel": "self", "type": "application/geo+json", "title": "0d1800b5-d842-4af3-846c-5d97ae3f0307", "name": "item", "description": "0d1800b5-d842-4af3-846c-5d97ae3f0307", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0d1800b5-d842-4af3-846c-5d97ae3f0307"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "/publisher", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:21Z", "type": "Dataset", "title": "Soil moisture and temperature datasets in LIDO orchard", "description": "Soil moisture and temperature timeserie datasets of the apple orchard located in the Laimburg Integrated Digital Orchard in Bolzano province. The timeseries collects data about soil moisture and temperature at 20 cm, 30 cm and 40 cm under the soil surface in 3 different position of the orchard. Acquisition frequency is 30 minutes for all the parameters.", "keywords": ["agricultural-and-aquaculture-facilities", "cct", "eu", "sensor", "soil", "soil-moisture", "temperature", "water"]}, "links": [{"href": "https://doi.org/10.48784/d41997c7-d9ea-4f10-bd2e-baf1d96bb8f8"}, {"href": "http://data.europa.eu/88u/dataset/d41997c7-d9ea-4f10-bd2e-baf1d96bb8f8"}, {"rel": "self", "type": "application/geo+json", "title": "/publisher", "name": "item", "description": "/publisher", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items//publisher"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "/", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:20Z", "type": "Dataset", "title": "DrSch\u00e4r mais field monitoring timeseries", "description": "Timeseries of the DrSch\u00e4r field monitoring in Este (PD) during summer 2022. Dataset of the soil temperature and soil humidity collected from different type of sensors distributed among the mais field. In the field were installed different types of sensors as many TDR sensors and one capacitive sensor; they collect temperature and humidity of the soil. The data from the sensor were collected by two networks: a Zigbee-based and one LoraWAN-based network.", "keywords": ["capacitive", "environmental-monitoring-facilities", "eu", "humidity", "irrigation", "lorawan", "mais", "sensor", "soil", "soil-moisture", "tdr", "temperature", "water", "zigbee"]}, "links": [{"href": "http://data.europa.eu/88u/dataset/17af841d-1329-4c5a-a8b8-c4326f0614f9"}, {"rel": "self", "type": "application/geo+json", "title": "/", "name": "item", "description": "/", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items//"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "000de6bf-6d6d-4f06-ac55-08862d635e47", "type": "Feature", "geometry": null, "properties": {"updated": "2025-07-07T11:20:35.373311Z", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-07-07 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-07-07 ore 00 UTC - Valido dalle ore 00 UTC del 2025-07-07 alle ore 00 UTC del 2025-07-10. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-07-07", "20250707t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-07-07-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250707T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250707T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250707T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250707T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250707T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250707T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250707T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250707T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/000de6bf-6d6d-4f06-ac55-08862d635e47"}, {"rel": "self", "type": "application/geo+json", "title": "000de6bf-6d6d-4f06-ac55-08862d635e47", "name": "item", "description": "000de6bf-6d6d-4f06-ac55-08862d635e47", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/000de6bf-6d6d-4f06-ac55-08862d635e47"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "00682004-c6b9-4c1d-8b40-3afff8bbec69", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[11.16, 47.52], [11.16, 47.52], [11.16, 47.52], [11.16, 47.52], [11.16, 47.52]]]}, "properties": {"themes": [{"concepts": [{"id": "climatologyMeteorologyAtmosphere"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "environmental factors"}, {"id": "water"}, {"id": "Soil analysis"}, {"id": "Soil"}, {"id": "soil amendments"}, {"id": "Soil biology"}, {"id": "Temperature profile"}, {"id": "moisture content"}, {"id": "Temperature"}, {"id": "Soil temperature"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "soil profile"}, {"id": "soil moisture"}, {"id": "temperature"}], "scheme": "GEMET - Concepts, version 2.4"}, {"concepts": [{"id": "farming systems"}, {"id": "Grassland management"}, {"id": "Grassland soils"}, {"id": "grasslands"}, {"id": "permanent grasslands"}, {"id": "agriculture"}, {"id": "agricultural practices"}, {"id": "Climatic change"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "Boden"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "opendata"}], "scheme": "Individual"}], "rights": "Restrictions applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations or warnings on using the resource or metadata. (e.g. Reports, articles, papers, scientific and non-scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \u201cData re-used from the BonaRes Data Centre www.bonares.de. This data were created as part of BonaRes Module A-Project - SUSALPS's research activities.\u201d Although every care has been taken in preparing and testing the data, BonaRes Module A-Project- SUSALPS and BonaRes Data Centre cannot guarantee that the data are correct; neither does BonaRes Module A-Project-SUSALPS and BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The BonaRes Module A-Project-SUSALPS and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data. The access to this data is restricted during embargo time. If prior access is requested, contact the data owner/author.)", "updated": "2020-02-14", "type": "Dataset", "created": "2018-12-05", "language": "eng", "title": "SUSALPS temperature and volumetric soil water content Esterberg Subplot 3 in Esterberg intensiv", "description": "Grassland is a precious good. Grassland contributes to food security by providing fodder for dairy and beef farming, storing nutrients and increasing biodiversity. These functions that secure the fertility and yields of soil are jeopardized by climate change, especially in monane and alpine areas.\nIn SUSALPS, scientists, authorities and farmers work together to investigate the influence of climate change on i) plant biodiversity, ii) C and N storage, iii) greenhouse gas exchange, iv) socio economic conditions that influence decision making of farmers.\nA central experimental aspect is the translocation of soil mesocosms from higher elevation to lower elevation (Esterberg site at 1200m, Graswang site at 860m, Fendt at 600m, Bayreuth at 300m). To reflect the spatial heterogeneity of soils, mesocosms from three different subplots approx. 100-300m apart from each other are translocated. Since temperatures are higher and precipitation is lower in lower elevation, the translocated mesocosms experience climate change.\nThis dataset contains daily average soil temperature and volumetric soil water content in 5 and 15 cm depth.\nTreatment: Esterberg Subplot 3 in Esterberg intensiv\nDevice: Decagon 5TM\nTimescale: Daily average\nDepths: 5 and 15 cm", "formats": [{"name": "CSV"}], "keywords": ["environmental factors", "water", "Soil analysis", "Soil", "soil amendments", "Soil biology", "Temperature profile", "moisture content", "Temperature", "Soil temperature", "soil profile", "soil moisture", "temperature", "farming systems", "Grassland management", "Grassland soils", "grasslands", "permanent grasslands", "agriculture", "agricultural practices", "Climatic change", "Boden", "opendata"], "contacts": [{"name": "Kiese, Ralf", "organization": "Karlsruhe Institute of Technology (KIT)", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "ralf.kiese@kit.edu"}], "addresses": [{"deliveryPoint": [null], "city": "Garmisch-Partenkirchen", "administrativeArea": null, "postalCode": "82467", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Kiese, Ralf", "organization": "Karlsruhe Institute of Technology (KIT)", "position": null, "roles": ["projectLeader"], "phones": [{"value": null}], "emails": [{"value": "ralf.kiese@kit.edu"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "BonaRes Data Centre", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "position": "Research Platform 'Data' - WG Geodata", "roles": ["publisher"], "phones": [{"value": "+49 33432 82 171"}], "emails": [{"value": "bonares-datenzentrum@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Strasse 84"], "city": "M\u00fcncheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": null}]}, {"organization": "Karlsruhe Institute of Technology (KIT)", "roles": ["contributor"]}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=00682004-c6b9-4c1d-8b40-3afff8bbec69", "rel": "download"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/217290dd-a23f-4734-96d5-71b878a2fca8", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "00682004-c6b9-4c1d-8b40-3afff8bbec69", "name": "item", "description": "00682004-c6b9-4c1d-8b40-3afff8bbec69", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/00682004-c6b9-4c1d-8b40-3afff8bbec69"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["2016-08-11T00:00:00Z", "2018-10-09T00:00:00Z"]}}, {"id": "00ec7fbc-a2df-466a-b1a8-a2fcfc6dc31e", "type": "Feature", "geometry": null, "properties": {"updated": "2025-05-26T06:33:50.348322Z", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-05-25 ore 12 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-05-25 ore 12 UTC - Valido dalle ore 12 UTC del 2025-05-25 alle ore 00 UTC del 2025-05-29. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["120000", "2025-05-25", "20250525t120000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN12/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-05-25-ore-12-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250525T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250525T120000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250525T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250525T120000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250525T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250525T120000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250525T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250525T120000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/00ec7fbc-a2df-466a-b1a8-a2fcfc6dc31e"}, {"rel": "self", "type": "application/geo+json", "title": "00ec7fbc-a2df-466a-b1a8-a2fcfc6dc31e", "name": "item", "description": "00ec7fbc-a2df-466a-b1a8-a2fcfc6dc31e", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/00ec7fbc-a2df-466a-b1a8-a2fcfc6dc31e"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "00fa75f3-0640-4096-b1ea-1287004ceadf", "type": "Feature", "geometry": null, "properties": {"updated": "2025-06-16T06:24:30.797077", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-06-15 ore 12 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-06-15 ore 12 UTC - Valido dalle ore 12 UTC del 2025-06-15 alle ore 00 UTC del 2025-06-19. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["120000", "2025-06-15", "20250615t120000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN12/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-06-15-ore-12-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250615T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250615T120000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250615T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250615T120000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250615T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250615T120000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250615T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250615T120000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/00fa75f3-0640-4096-b1ea-1287004ceadf"}, {"rel": "self", "type": "application/geo+json", "title": "00fa75f3-0640-4096-b1ea-1287004ceadf", "name": "item", "description": "00fa75f3-0640-4096-b1ea-1287004ceadf", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/00fa75f3-0640-4096-b1ea-1287004ceadf"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "02e48008-3f6b-4344-b410-f8421981fee8", "type": "Feature", "geometry": null, "properties": {"updated": "2025-07-04T06:20:31.377838", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-07-03 ore 12 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-07-03 ore 12 UTC - Valido dalle ore 12 UTC del 2025-07-03 alle ore 00 UTC del 2025-07-07. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["120000", "2025-07-03", "20250703t120000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN12/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-07-03-ore-12-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250703T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250703T120000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250703T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250703T120000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250703T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250703T120000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250703T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250703T120000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/02e48008-3f6b-4344-b410-f8421981fee8"}, {"rel": "self", "type": "application/geo+json", "title": "02e48008-3f6b-4344-b410-f8421981fee8", "name": "item", "description": "02e48008-3f6b-4344-b410-f8421981fee8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/02e48008-3f6b-4344-b410-f8421981fee8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "034b94b8-dee4-4315-bbf1-eb562f54943c", "type": "Feature", "geometry": null, "properties": {"updated": "2025-06-16T11:26:27.268672", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-06-16 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-06-16 ore 00 UTC - Valido dalle ore 00 UTC del 2025-06-16 alle ore 00 UTC del 2025-06-19. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-06-16", "20250616t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-06-16-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250616T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250616T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250616T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250616T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250616T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250616T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250616T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250616T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/034b94b8-dee4-4315-bbf1-eb562f54943c"}, {"rel": "self", "type": "application/geo+json", "title": "034b94b8-dee4-4315-bbf1-eb562f54943c", "name": "item", "description": "034b94b8-dee4-4315-bbf1-eb562f54943c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/034b94b8-dee4-4315-bbf1-eb562f54943c"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "049993df-7f91-4a53-8dd9-4b3e0c1cd3bb", "type": "Feature", "geometry": null, "properties": {"updated": "2025-06-22T09:23:24.409913", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-06-22 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-06-22 ore 00 UTC - Valido dalle ore 00 UTC del 2025-06-22 alle ore 00 UTC del 2025-06-25. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-06-22", "20250622t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-06-22-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250622T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250622T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250622T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250622T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250622T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250622T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250622T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250622T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/049993df-7f91-4a53-8dd9-4b3e0c1cd3bb"}, {"rel": "self", "type": "application/geo+json", "title": "049993df-7f91-4a53-8dd9-4b3e0c1cd3bb", "name": "item", "description": "049993df-7f91-4a53-8dd9-4b3e0c1cd3bb", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/049993df-7f91-4a53-8dd9-4b3e0c1cd3bb"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "05a760dc-1cbf-4710-a8ea-caa0637ffe47", "type": "Feature", "geometry": null, "properties": {"updated": "2025-04-24T13:25:19.463786", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-04-24 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-04-24 ore 00 UTC - Valido dalle ore 00 UTC del 2025-04-24 alle ore 00 UTC del 2025-04-27. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-04-24", "20250424t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-04-24-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250424T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250424T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250424T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250424T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250424T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250424T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250424T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250424T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/05a760dc-1cbf-4710-a8ea-caa0637ffe47"}, {"rel": "self", "type": "application/geo+json", "title": "05a760dc-1cbf-4710-a8ea-caa0637ffe47", "name": "item", "description": "05a760dc-1cbf-4710-a8ea-caa0637ffe47", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/05a760dc-1cbf-4710-a8ea-caa0637ffe47"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "06349de3-bb25-48e5-a048-4a2b93550063", "type": "Feature", "geometry": null, "properties": {"updated": "2025-07-13T11:24:22.624376", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-07-13 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-07-13 ore 00 UTC - Valido dalle ore 00 UTC del 2025-07-13 alle ore 00 UTC del 2025-07-16. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-07-13", "20250713t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-07-13-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250713T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250713T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250713T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250713T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250713T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250713T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250713T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250713T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/06349de3-bb25-48e5-a048-4a2b93550063"}, {"rel": "self", "type": "application/geo+json", "title": "06349de3-bb25-48e5-a048-4a2b93550063", "name": "item", "description": "06349de3-bb25-48e5-a048-4a2b93550063", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/06349de3-bb25-48e5-a048-4a2b93550063"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "07388e86-f38b-469a-9910-6e24af66bbf5", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[11.07, 47.83], [11.07, 47.83], [11.07, 47.83], [11.07, 47.83], [11.07, 47.83]]]}, "properties": {"themes": [{"concepts": [{"id": "climatologyMeteorologyAtmosphere"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "environmental factors"}, {"id": "water"}, {"id": "Soil analysis"}, {"id": "Soil"}, {"id": "soil amendments"}, {"id": "Soil biology"}, {"id": "Temperature profile"}, {"id": "moisture content"}, {"id": "Temperature"}, {"id": "Soil temperature"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "soil profile"}, {"id": "soil moisture"}, {"id": "temperature"}], "scheme": "GEMET - Concepts, version 2.4"}, {"concepts": [{"id": "farming systems"}, {"id": "Grassland management"}, {"id": "Grassland soils"}, {"id": "grasslands"}, {"id": "permanent grasslands"}, {"id": "agriculture"}, {"id": "agricultural practices"}, {"id": "Climatic change"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "Boden"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "opendata"}], "scheme": "Individual"}], "rights": "Restrictions applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations or warnings on using the resource or metadata. (e.g. Reports, articles, papers, scientific and non-scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \u201cData re-used from the BonaRes Data Centre www.bonares.de. This data were created as part of BonaRes Module A-Project - SUSALPS's research activities.\u201d Although every care has been taken in preparing and testing the data, BonaRes Module A-Project- SUSALPS and BonaRes Data Centre cannot guarantee that the data are correct; neither does BonaRes Module A-Project-SUSALPS and BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The BonaRes Module A-Project-SUSALPS and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data. The access to this data is restricted during embargo time. If prior access is requested, contact the data owner/author.)", "updated": "2020-02-14", "type": "Dataset", "created": "2018-12-05", "language": "eng", "title": "SUSALPS temperature and volumetric soil water content Graswang Subplot 1 in Fendt intensiv", "description": "Grassland is a precious good. Grassland contributes to food security by providing fodder for dairy and beef farming, storing nutrients and increasing biodiversity. These functions that secure the fertility and yields of soil are jeopardized by climate change, especially in monane and alpine areas. In SUSALPS, scientists, authorities and farmers work together to investigate the influence of climate change on i) plant biodiversity, ii) C and N storage, iii) greenhouse gas exchange, iv) socio economic conditions that influence decision making of farmers. A central experimental aspect is the translocation of soil mesocosms from higher elevation to lower elevation (Esterberg site at 1200m, Graswang site at 860m, Fendt at 600m, Bayreuth at 300m). To reflect the spatial heterogeneity of soils, mesocosms from three different subplots approx. 100-300m apart from each other are translocated. Since temperatures are higher and precipitation is lower in lower elevation, the translocated mesocosms experience climate change. This dataset contains daily average soil temperature and volumetric soil water content in 5 and 15 cm depth. Treatment: Graswang Subplot 1 in Fendt intensiv Device: Decagon 5TM Timescale: Daily average Depths: 5 and 15 cm", "formats": [{"name": "CSV"}], "keywords": ["environmental factors", "water", "Soil analysis", "Soil", "soil amendments", "Soil biology", "Temperature profile", "moisture content", "Temperature", "Soil temperature", "soil profile", "soil moisture", "temperature", "farming systems", "Grassland management", "Grassland soils", "grasslands", "permanent grasslands", "agriculture", "agricultural practices", "Climatic change", "Boden", "opendata"], "contacts": [{"name": "Kiese, Ralf", "organization": "Karlsruhe Institute of Technology (KIT)", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "ralf.kiese@kit.edu"}], "addresses": [{"deliveryPoint": [null], "city": "Garmisch-Partenkirchen", "administrativeArea": null, "postalCode": "82467", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Kiese, Ralf", "organization": "Karlsruhe Institute of Technology (KIT)", "position": null, "roles": ["projectLeader"], "phones": [{"value": null}], "emails": [{"value": "ralf.kiese@kit.edu"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"name": "BonaRes Data Centre", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "position": "Research Platform 'Data' - WG Geodata", "roles": ["publisher"], "phones": [{"value": "+49 33432 82 171"}], "emails": [{"value": "bonares-datenzentrum@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Strasse 84"], "city": "M\u00fcncheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": null}]}, {"organization": "Karlsruhe Institute of Technology (KIT)", "roles": ["contributor"]}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=07388e86-f38b-469a-9910-6e24af66bbf5", "rel": "download"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/217290dd-a23f-4734-96d5-71b878a2fca8", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "07388e86-f38b-469a-9910-6e24af66bbf5", "name": "item", "description": "07388e86-f38b-469a-9910-6e24af66bbf5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/07388e86-f38b-469a-9910-6e24af66bbf5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["2016-08-11T00:00:00Z", "2018-10-09T00:00:00Z"]}}, {"id": "10.1002/joc.1276", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:31Z", "type": "Journal Article", "created": "2005-11-30", "title": "Very High Resolution Interpolated Climate Surfaces For Global Land Areas", "description": "(Uploaded by Plazi for the Bat Literature Project) We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950\u20132000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a higher spatial resolution (400 times greater or more); more weather station records were used; improved elevation data were used; and more information about spatial patterns of uncertainty in the data is available. Owing to the overall low density of available climate stations, our surfaces do not capture of all variation that may occur at a resolution of 1 km, particularly of precipitation in mountainous areas. In future work, such variation might be captured through knowledgebased methods and inclusion of additional co-variates, particularly layers obtained through remote sensing. Copyright \uf6d9 2005 Royal Meteorological Society.", "keywords": ["0106 biological sciences", "0301 basic medicine", "550", "Climate", "bats", "bat", "Precipitation", "precipitation", "01 natural sciences", "Error", "geographical information systems", "03 medical and health sciences", "precipitaci\u00f3n atmosf\u00e9rica", "Chiroptera", "1902 Atmospheric Science", "Animalia", "Chordata", "temperatura", "factores clim\u00e1ticos", "procesamiento de datos", "Temperature", "Uncertainty", "temperature", "Biodiversity", "15. Life on land", "GIS", "climatic factors", "Interpolation", "ANUSPLIN", "13. Climate action", "Mammalia", "sistemas de informaci\u00f3n geogr\u00e1fica", "data processing"]}, "links": [{"href": "https://doi.org/10.1002/joc.1276"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Journal%20of%20Climatology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/joc.1276", "name": "item", "description": "10.1002/joc.1276", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/joc.1276"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2005-01-01T00:00:00Z"}}, {"id": "08256657-2999-4917-b973-669e7047a784", "type": "Feature", "geometry": null, "properties": {"updated": "2025-07-15T06:22:33.018923", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-07-14 ore 12 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-07-14 ore 12 UTC - Valido dalle ore 12 UTC del 2025-07-14 alle ore 00 UTC del 2025-07-18. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["120000", "2025-07-14", "20250714t120000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN12/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-07-14-ore-12-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250714T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250714T120000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250714T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250714T120000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250714T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250714T120000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250714T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250714T120000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/08256657-2999-4917-b973-669e7047a784"}, {"rel": "self", "type": "application/geo+json", "title": "08256657-2999-4917-b973-669e7047a784", "name": "item", "description": "08256657-2999-4917-b973-669e7047a784", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/08256657-2999-4917-b973-669e7047a784"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "0902.0343", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:24Z", "type": "Report", "title": "Local Structure of La1-xSrxCoO3 determined from EXAFS and neutron PDF studies", "description": "Open AccessThe combined local structure techniques, extended x-ray absorption fine structure (EXAFS) and neutron pair distribution function analysis, have been used for temperatures 4 <= T <= 330 K to rule out a large Jahn-Teller (JT) distortion of the Co-O bond in La1-xSrxCoO3 for a significant fraction of Co sites (x <= 0.35), indicating few, if any, JT-active, singly occupied e_g Co sites exist.", "keywords": ["Colbaltites", "Jahn-Teller", "Neutrons", "Distribution Functions", "Strontium Oxides", "75", "Strongly Correlated Electrons (cond-mat.str-el)", "Local Structure", "FOS: Physical sciences", "36", "530", "Cobalt Oxides", "Absorption", "Condensed Matter - Strongly Correlated Electrons", "Lanthanum Oxides", "Neutrons Local Structure", "Temperature Range 0273-0400 K", "Fine Structure"], "contacts": [{"organization": "Sundaram, N., Jiang, Y., Anderson, I. E., Belanger, D. P., Booth, C. H., Bridges, F., Mitchell, J. F., Proffen, Th., Zheng, H.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/0902.0343"}, {"rel": "self", "type": "application/geo+json", "title": "0902.0343", "name": "item", "description": "0902.0343", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0902.0343"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-01-01T00:00:00Z"}}, {"id": "09475c2d-3325-4602-a3c3-c00858653f8f", "type": "Feature", "geometry": null, "properties": {"updated": "2025-05-15T11:21:53.081992", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-05-15 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-05-15 ore 00 UTC - Valido dalle ore 00 UTC del 2025-05-15 alle ore 00 UTC del 2025-05-18. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-05-15", "20250515t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-05-15-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250515T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250515T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250515T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250515T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250515T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250515T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250515T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250515T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/09475c2d-3325-4602-a3c3-c00858653f8f"}, {"rel": "self", "type": "application/geo+json", "title": "09475c2d-3325-4602-a3c3-c00858653f8f", "name": "item", "description": "09475c2d-3325-4602-a3c3-c00858653f8f", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/09475c2d-3325-4602-a3c3-c00858653f8f"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "0a17569a-4c6c-44e3-85f7-f6f260b2092c", "type": "Feature", "geometry": null, "properties": {"updated": "2025-05-15T06:22:09.070865Z", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-05-14 ore 12 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-05-14 ore 12 UTC - Valido dalle ore 12 UTC del 2025-05-14 alle ore 00 UTC del 2025-05-18. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["120000", "2025-05-14", "20250514t120000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN12/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-05-14-ore-12-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250514T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250514T120000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250514T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250514T120000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250514T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250514T120000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250514T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250514T120000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/0a17569a-4c6c-44e3-85f7-f6f260b2092c"}, {"rel": "self", "type": "application/geo+json", "title": "0a17569a-4c6c-44e3-85f7-f6f260b2092c", "name": "item", "description": "0a17569a-4c6c-44e3-85f7-f6f260b2092c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0a17569a-4c6c-44e3-85f7-f6f260b2092c"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "0a615ceb-1204-495a-bd07-6233987837e5", "type": "Feature", "geometry": null, "properties": {"updated": "2025-08-12T06:20:33.654348", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-08-11 ore 12 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-08-11 ore 12 UTC - Valido dalle ore 12 UTC del 2025-08-11 alle ore 00 UTC del 2025-08-15. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["120000", "2025-08-11", "20250811t120000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN12/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-08-11-ore-12-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250811T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250811T120000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250811T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250811T120000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250811T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250811T120000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250811T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250811T120000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/0a615ceb-1204-495a-bd07-6233987837e5"}, {"rel": "self", "type": "application/geo+json", "title": "0a615ceb-1204-495a-bd07-6233987837e5", "name": "item", "description": "0a615ceb-1204-495a-bd07-6233987837e5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0a615ceb-1204-495a-bd07-6233987837e5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "0ae13043-e97b-4898-ba85-2ed437b88deb", "type": "Feature", "geometry": null, "properties": {"updated": "2025-09-01T11:20:50.325057", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-09-01 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-09-01 ore 00 UTC - Valido dalle ore 00 UTC del 2025-09-01 alle ore 00 UTC del 2025-09-04. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-09-01", "20250901t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-09-01-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250901T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250901T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250901T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250901T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250901T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250901T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250901T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250901T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/0ae13043-e97b-4898-ba85-2ed437b88deb"}, {"rel": "self", "type": "application/geo+json", "title": "0ae13043-e97b-4898-ba85-2ed437b88deb", "name": "item", "description": "0ae13043-e97b-4898-ba85-2ed437b88deb", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0ae13043-e97b-4898-ba85-2ed437b88deb"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "0b3fed9b6a7790a67cc733e73de3c4d7", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:26Z", "type": "Report", "title": "Winters are changing: Snow effects on Arctic and alpine tundra ecosystems", "keywords": ["tundra", "ground temperatures", "ITEX", "13. Climate action", "review", "15. Life on land", "snow experiments"], "contacts": [{"organization": "Rixen, Christian, H\u00f8ye, Toke Thomas, Macek, Petr, Aerts, Rien, Alatalo, Juha, Anderson, Jill T., Arnold, Pieter A., Barrio, Isabel C., Bjerke, Jarle W., Bj\u00f6rkman, Mats P., Blok, Daan, Blume-Werry, Gesche, Boike, Julia, Bokhorst, Stef, Carbognani, Michele, Christiansen, Casper T., Convey, Peter, Cooper, Elisabeth J., Cornelissen, Hans C., Coulson, Stephen J., Dorrepaal, Ellen, Elberling, Bo, Elmendorf, Sarah, Elphinstone, Cassandra, Frei, Esther, Geange, Sonya, Gehrmann, Friederike, Gibson, Casey, Grogan, Paul, Harte, John, Henry, Greg, Inouye, David, Irwin, Rebecca, Jespersen, Gus, J\u00f3nsd\u00f3ttir, Ingibj\u00f6rg Svala, Jung, Ji Young, Klinge, David, Kudo, Gaku, L\u00e4ms\u00e4, Juho, Lee, Hanna, Lembrechts, Jonas, Lett, Signe, Mann, Hjalte Mads, Mastepanov, Mikhail, Morse, Jennifer, Myers-Smith, Isla, Olofsson, Johan, Paavola, Riku, Petraglia, Alessandro, Phoenix, Gareth K., Semenchuk, Philipp, Siewert, Matthias B., Slatyer, Rachel, Spasojevic, Marko, Suding, Katharine, Sullivan, Patrick, Thompson, Kimberly, V\u00e4is\u00e4nen, Maria, Vandvik, Vigdis, Venn, Susanna, Walz, Josefine, Way, Robert, Welker, Jeffrey M., Whittingham Forte, T'ai Gladys, Wipf, Sonja, Zong, Shengwei,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/0b3fed9b6a7790a67cc733e73de3c4d7"}, {"rel": "self", "type": "application/geo+json", "title": "0b3fed9b6a7790a67cc733e73de3c4d7", "name": "item", "description": "0b3fed9b6a7790a67cc733e73de3c4d7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0b3fed9b6a7790a67cc733e73de3c4d7"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-09-01T00:00:00Z"}}, {"id": "0cbdb159-04ee-4e70-8412-e4a984c5d91b", "type": "Feature", "geometry": null, "properties": {"updated": "2025-09-16T11:24:26.466772", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-09-16 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-09-16 ore 00 UTC - Valido dalle ore 00 UTC del 2025-09-16 alle ore 00 UTC del 2025-09-19. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-09-16", "20250916t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-09-16-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250916T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250916T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250916T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250916T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250916T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250916T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250916T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250916T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/0cbdb159-04ee-4e70-8412-e4a984c5d91b"}, {"rel": "self", "type": "application/geo+json", "title": "0cbdb159-04ee-4e70-8412-e4a984c5d91b", "name": "item", "description": "0cbdb159-04ee-4e70-8412-e4a984c5d91b", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0cbdb159-04ee-4e70-8412-e4a984c5d91b"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "0d41a483-52b2-464f-b526-3ae29e6ad089", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[12.99, 52.98], [12.99, 53.15], [13.64, 53.15], [13.64, 52.98], [12.99, 52.98]]]}, "properties": {"rights": "Restrictions applied to assure the protection of privacy or intellectual property, and any special restrictions or limitations or warnings on using the resource or metadata. Reports, articles, papers, scientific and non - scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \"Data reused from the BonaRes Data Centre www.bonares.de. This data were created as part of the ZALF Datenerfassung's research activities.\" Although every care has been taken in preparing and testing the data, the ZALF Datenerfassung and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the ZALF Datenerfassung and the BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The ZALF Datenerfassung and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data.", "updated": "2024-02-05", "type": "Service", "created": "2023-11-28", "language": "eng", "title": "Web Map Service of the dataset 'Data on soil respiration in a beech forest and a pine forest'", "description": "This Web Map Service includes spatial information used by the dataset 'Data on soil respiration in a beech forest and a pine forest''", "keywords": ["infoMapAccessService", "Soil", "soil respiration", "soil air", "soil temperature", "soil water content", "Fagus sylvatica", "Pinus sylvestris", "measurement", "Soil", "soil respiration", "soil air", "soil temperature", "soil water content", "Fagus sylvatica", "Pinus sylvestris", "measurement", "Germany", "Brandenburg", "Barnim", "Ostprignitz-Ruppin"], "contacts": [{"name": "Leibniz Centre for Agricultural Landscape Research", "organization": "ZALF", "position": "Research Platform 'Data Analysis & Simulation' - Workgroup Research Data Management", "roles": ["publisher"], "phones": [{"value": "+49 33432 82 300"}], "emails": [{"value": "dataservice@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Strasse 84"], "city": "M\u00fcncheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "https://ror.org/01ygyzs83", "name_url": "", "description": "ROR", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Hubert Jochheim", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "Hubert.jochheim@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0001-8047-4553", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Stephan Wirth", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "position": null, "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "swirth@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0001-8047-4553", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Hubert Jochheim", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "position": null, "roles": ["projectLeader"], "phones": [{"value": null}], "emails": [{"value": "Hubert.jochheim@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0001-8047-4553", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Valentin Gartiser", "organization": "Georg-August-Universit\u00e4t G\u00f6ttingen", "position": null, "roles": ["researcher"], "phones": [{"value": null}], "emails": [{"value": "valentin.gartiser@stud.uni-goettingen.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0001-5320-374X", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Martin Maier", "organization": "Georg-August-Universit\u00e4t G\u00f6ttingen", "position": null, "roles": ["researcher"], "phones": [{"value": null}], "emails": [{"value": "martin.maier@uni-goettingen.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": "0000-0002-7959-0108", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Dieter Sowa", "organization": "Leibniz Centre for Agricultural Landscape Research", "position": null, "roles": ["dataCollector"], "phones": [{"value": null}], "emails": [{"value": "Annett.Stange@zalf.de"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "roles": ["contributor"]}], "themes": [{"concepts": [{"id": "infoMapAccessService"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "Soil"}, {"id": "soil respiration"}, {"id": "soil air"}, {"id": "soil temperature"}, {"id": "soil water content"}, {"id": "Fagus sylvatica"}, {"id": "Pinus sylvestris"}, {"id": "measurement"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "Soil"}, {"id": "soil respiration"}, {"id": "soil air"}, {"id": "soil temperature"}, {"id": "soil water content"}, {"id": "Fagus sylvatica"}, {"id": "Pinus sylvestris"}, {"id": "measurement"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "Germany"}, {"id": "Brandenburg"}, {"id": "Barnim"}, {"id": "Ostprignitz-Ruppin"}], "scheme": "individual"}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=0d41a483-52b2-464f-b526-3ae29e6ad089", "rel": "information"}, {"href": "https://maps.bonares.de/wss/service/ags-relay/ags/guest/arcgis/rest/services/Zalf/ID_4731_both_sites/MapServer/WMSServer?request=GetCapabilities&service=WMS"}, {"rel": "self", "type": "application/geo+json", "title": "0d41a483-52b2-464f-b526-3ae29e6ad089", "name": "item", "description": "0d41a483-52b2-464f-b526-3ae29e6ad089", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0d41a483-52b2-464f-b526-3ae29e6ad089"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-02-05T00:00:00Z"}}, {"id": "10.1002/2015gb005239", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:28Z", "type": "Journal Article", "created": "2015-12-19", "title": "Toward More Realistic Projections Of Soil Carbon Dynamics By Earth System Models", "description": "Abstract

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real\uffe2\uff80\uff90world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first\uffe2\uff80\uff90order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth\uffe2\uff80\uff90dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool\uffe2\uff80\uff90 and flux\uffe2\uff80\uff90based data sets through data assimilation is among the highest priorities for near\uffe2\uff80\uff90term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

", "keywords": ["550", "LAND MODELS", "Oceanography", "HETEROTROPHIC RESPIRATION", "01 natural sciences", "Atmospheric Sciences", "LITTER DECOMPOSITION", "ORGANIC-CARBON", "Geoinformatics", "GLOBAL CLIMATE-CHANGE", "DATA-ASSIMILATION", "Meteorology & Atmospheric Sciences", "TEMPERATURE SENSITIVITY", "CMIP5", "MICROBIAL MODELS", "0105 earth and related environmental sciences", "2. Zero hunger", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "500", "Earth system models", "04 agricultural and veterinary sciences", "15. Life on land", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "TERRESTRIAL ECOSYSTEMS", "Climate Action", "Geochemistry", "Climate change impacts and adaptation", "realistic projections", "13. Climate action", "recommendations", "Earth Sciences", "0401 agriculture", " forestry", " and fisheries", "soil carbon dynamics", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Climate Change Impacts and Adaptation", "Environmental Sciences", "PARAMETER-ESTIMATION"]}, "links": [{"href": "https://escholarship.org/content/qt1pw7g2r2/qt1pw7g2r2.pdf"}, {"href": "https://doi.org/10.1002/2015gb005239"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Biogeochemical%20Cycles", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/2015gb005239", "name": "item", "description": "10.1002/2015gb005239", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2015gb005239"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-01T00:00:00Z"}}, {"id": "10.1002/2016rg000543", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:28Z", "type": "Journal Article", "created": "2017-03-23", "title": "A review of spatial downscaling of satellite remotely sensed soil moisture", "description": "Abstract

Satellite remote sensing technology has been widely used to estimate surface soil moisture. Numerous efforts have been devoted to develop global soil moisture products. However, these global soil moisture products, normally retrieved from microwave remote sensing data, are typically not suitable for regional hydrological and agricultural applications such as irrigation management and flood predictions, due to their coarse spatial resolution. Therefore, various downscaling methods have been proposed to improve the coarse resolution soil moisture products. The purpose of this paper is to review existing methods for downscaling satellite remotely sensed soil moisture. These methods are assessed and compared in terms of their advantages and limitations. This review also provides the accuracy level of these methods based on published validation studies. In the final part, problems and future trends associated with these methods are analyzed.The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation\uffc2\uffa0modelling was clearly higher for the spatial variability of N\uffe2\uff80\uff90 than for C\uffe2\uff80\uff90 and P\uffe2\uff80\uff90related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change.Understanding anthropogenic influences on soil respiration (Rs) is critical for accurate predictions of soil carbon fluxes, but it is not known how Rs responds to grazing exclusion (GE). Here, we conducted a manipulative experiment in a meadow grassland on the Tibetan Plateau to investigate the effects of GE on Rs. The exclusion of livestock significantly increased soil moisture and above\uffe2\uff80\uff90ground biomass, but it decreased soil temperature, microbial biomass carbon (MBC), and Rs. Regression analysis indicated that the effects of GE on Rs were mainly due to changes in soil temperature, soil moisture, and MBC. Compared with the grazed blocks, GE significantly decreased soil carbon release by 23.6% over the growing season and 21.4% annually, but it increased the temperature sensitivity (Q10) of Rs by 6.5% and 14.2% for the growing season and annually respectively. Therefore, GE may reduce the release of soil carbon from the Tibetan Plateau, but under future climate warming scenarios, the increases in Q10 induced by GE could lead to increased carbon emissions.

", "keywords": ["570", "MICROBIAL RESPIRATION", "Environmental Sciences & Ecology", "Plant Productivity", "Temperature Sensitivity", "ALPINE GRASSLAND", "630", "Microbial Biomass Carbon", "NORTHERN CHINA", "SEASONAL PATTERNS", "MOUNTAIN GRASSLANDS", "Grazing Exclusion", "Tibetan Plateau", "PLANT-COMMUNITIES", "Original Research", "2. Zero hunger", "Science & Technology", "CLIMATE-CHANGE", "CO2 EFFLUX", "Ecology", "04 agricultural and veterinary sciences", "15. Life on land", "INNER-MONGOLIA", "BELOW-GROUND BIOMASS", "Soil Respiration", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "Life Sciences & Biomedicine"]}, "links": [{"href": "https://doi.org/10.1002/ece3.1867"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecology%20and%20Evolution", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/ece3.1867", "name": "item", "description": "10.1002/ece3.1867", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/ece3.1867"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-11T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=TEMPERATURE&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=TEMPERATURE&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=TEMPERATURE&", "hreflang": "en-US"}, {"rel": "next", "type": "application/geo+json", "title": "items (next)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=TEMPERATURE&offset=50", "hreflang": "en-US"}], "numberMatched": 727, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-10-23T04:54:54.681562Z"}